Ingeniería Biomédica
2026-01-14
Definition
The digital image
If the coordinates and the intensity are discrete quantities the image turns into a digital image.
Definition
A digital image is composed by a finite number of elements called PIXEL.
Depth
A digital image is composed by a finite number of elements called PIXEL. Bpp( Bits per pixel)
Color Space
How can i represent the color
Important
We also understand that light is a type of electromagnetic radiation, and its wavelength falls within a range from 400 nanometers to 700 nanometers.
Taken from Corke 2023
Important
The most common way light is made is by something getting really hot. This makes energy that comes out as light.
Some important term are:
The eye
The artificial eye
The currents from each sensor are function of the luminance and the spectral response filter.
Taken from https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf
Taken from https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf
Taken from https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf
Taken from https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf
Taken from https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf
Definition
Sampling: Digitalization of the spatial coordinates.
Definition
Quantiazation: Digitalization of the light intensity (amplitude).
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
From normal to linear
\[\alpha = My+x\]
From linear to normal
\[x = \alpha \bmod M\]
\[y = \frac{\alpha - x}{M}\]
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
Tomado de Gonzalez, Rafael C., y Richard E. Woods. 2018. Digital Image Processing. New York, NY: Pearson.
Tomado de https://medium.com/@abhishekjainindore24/semantic-vs-instance-vs-panoptic-segmentation-b1f5023da39f
Tomado de https://medium.com/@abhishekjainindore24/semantic-vs-instance-vs-panoptic-segmentation-b1f5023da39f
Neighborhood
Neighborhood
Rules for adjecency
4-Adjecncy: Two pixels p and q with values from V are 4-adjacent if q is in the set \(N_4\left(p\right)\)
8-adjacency. Two pixels p and q with values from V are 8-adjacent if q is in the set \(N_8\left(p\right)\)
m-adjacency (also called mixed adjacency). Two pixels p and q with values from V are m-adjacent if:
Adjacency
Digital path
It is a sequence of adjacent pixels.
\[\left(x_0, y_0\right), \left(x_1, y_1\right), \left(x_2, y_2\right), \dots \left(x_n, y_n\right)\]
If \(\left(x_0, y_0\right)=\left(x_n, y_n\right)\) the path is known as closed path
Let S represent a subset of pixels in an image. Two pixels p and q are said to be connected in S if there exists a path between them consisting entirely of pixels in S.